Previous fracture and subsequent fracture risk: A meta-analysis to update FRAX

Summary A large international meta-analysis using primary data from 64 cohorts has quantified the increased risk of fracture associated with a previous history of fracture for future use in FRAX. Introduction The aim of this study was to quantify the fracture risk associated with a prior fracture on an international basis and to explore the relationship of this risk with age, sex, time since baseline and bone mineral density (BMD). Methods We studied 665,971 men and 1,438,535 women from 64 cohorts in 32 countries followed for a total of 19.5 million person-years. The effect of a prior history of fracture on the risk of any clinical fracture, any osteoporotic fracture, major osteoporotic fracture and hip fracture alone was examined using an extended Poisson model in each cohort. Covariates examined were age, sex, BMD and duration of follow up. The results of the different studies were merged by using the weighted β-coefficients. Results A previous fracture history, compared with individuals without a prior fracture, was associated with a significantly increased risk of any clinical fracture (Hazard ratio, HR = 1.88; 95% CI = 1.72-2.07). The risk ratio was similar for the outcome of osteoporotic fracture (HR = 1.87; 95% CI = 1.69-2.07), major osteoporotic fracture (HR = 1.83; 95% CI = 1.63-2.06) or for hip fracture (HR = 1.82; 95% CI = 1.62-2.06). There was no significant difference in risk ratio between men and women. Subsequent fracture risk was marginally downward adjusted when account was taken of BMD. Low BMD explained a minority of the risk for any clinical fracture (14%), osteoporotic fracture (17%), and for hip fracture (33%). The risk ratio for all fracture outcomes related to prior fracture decreased significantly with adjustment for age and time since baseline examination. Conclusion A previous history of fracture confers an increased risk of fracture of substantial importance beyond that explained by BMD. The effect is similar in men and women. Its quantitation on an international basis permits the more accurate use of this risk factor in case finding strategies.


Introduction
A history of a prior fracture at a site characteristic for osteoporosis is an important risk factor for further fracture [1][2][3][4][5][6].Fracture risk is approximately doubled in the presence of a prior fracture, including morphometric vertebral fractures.The risks are in part independent of BMD [4].However, the increase in risk is not constant with age.For example, a large meta-analysis showed that a prior fracture history was a significant risk factor for hip fracture at all ages, but the population relative risk was highest at younger ages and decreased progressively with age [4].
The identification of patients with a fracture history is a well-established goal in the clinical management of osteoporosis as outlined in most clinical guidelines worldwide [7][8][9][10][11][12].In many cases, individuals with a prior fracture are eligible for treatment irrespective of BMD.For example, the National Osteoporosis Guideline Group (NOGG) in the UK recommends treatment in all women with a prior fragility fracture [10].A similar threshold is provided in the European guidance [13].In the USA, a prior vertebral or hip fracture qualifies for a treatment recommendation irrespective of BMD [14].
Because a prior fracture provides a fracture risk that is largely independent of BMD, it has been incorporated into assessment guidelines that integrate the risks associated with a number of risk variables [15][16][17].FRAX®, currently available in 78 territories, is the most widely used fracture risk assessment tool and is incorporated into a large number of assessment guidelines [7], recommended by the Committee for Medicinal Products for Human Use (CHMP) [18], and approved by the National Institute for Health and Care Excellence (NICE) [19].The incorporation of a prior fracture as an input variable for risk prediction was based on a meta-analysis, published in 2004, of 15,259 men and 44,902 women from 11 cohorts followed for a total of 250,000 person-years [4].Since then, many more prospectively studied cohorts have become available that have the potential to improve the accuracy of FRAX [20].
The aim of the present study was to quantify the risk for future fracture associated with a history of prior fracture in an international setting and to explore the dependence of this risk on age, sex, time since baseline assessment and BMD.

Methods
The study population was derived from a systematic review that identified prospective cohort studies for the update of FRAX.The study was registered with the International prospective register of systematic reviews, PROSPERO (CRD42021227266), and followed the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines.Studies were eligible if the cohort was prospective, included at least 200 participants, assessed an adequate number of clinical risk factors, and reported an adequate number of incident fracture outcomes.We studied 2,104,506 men and women from 64 prospectively studied cohorts of whom 9.7% had a prior fracture history.Fifty-eight cohorts included women (n = 1,438,535) and 40 cohorts included men (n = 665,971).Details of the cohorts studied have been given previously [20] and are summarized in Table 1.

Baseline and outcome variables
The construct of the question to determine a prior fracture history differed between the cohorts studied, based on time of previous fracture, fracture site, energy, validity, and inclusion of morphometric vertebral fractures (Table 2).
For outcomes, information on all clinical fractures was used for this report "all fractures."In addition, fractures considered to be associated with osteoporosis were examined [21].According to this classification, fractures of the skull, face, hands, feet, ankle, and patella were excluded as well as tibial and fibular fractures in men.Hip fracture and major osteoporotic fracture were also analyzed separately.No distinction was made according to trauma since both high-and low-trauma fractures show similar relationships with low BMD and future fracture risk [22].The risk of death as function of fracture history was also assessed.

Statistical methods
The risk of fracture was estimated by an extended Poisson model applied separately to each cohort (and also separately by sex for those cohorts with both men and women) [23,24].Because of an embargo on transfer of primary data from Manitoba, Cox regression was used on the Manitoba cohort on site and beta-coefficients, variances, and covariances forwarded to the analysis team.Covariates included current time since start of follow-up, current age (derived from age at since start of follow-up and current time since start of follow-up), prior history of fracture, and BMD at the femoral neck.Femoral neck BMD was adjusted for manufacturer and T-scores were calculated from the NHANES III White female reference values [20].We additionally estimated a model that excluded BMD from the covariates.A further model included the interaction term "prior fracture• current time since baseline" to determine whether the strength of the association of prior fracture and fracture risk changed with time.An additional model included the interaction term "prior fracture• current age" to determine whether the   The HR of those with a prior fracture history versus those without a prior fracture history was equal to e weighted mean of β .There was significant heterogeneity in risk between cohorts (index of heterogeneity I 2 = 82-98% depending on fracture outcome), and a random effects model was used in the meta-analysis.
The component of the risk ratio explained by BMD was computed from a meta-analysis of BMD and fracture risk in men and women combined [25].Based on the prior evidence, the risk of any clinical fracture was assumed to increase 1.45-fold for each SD decrease in BMD at the femoral neck.For hip fracture, the gradient of risk was assumed to be 2.07 per SD and 1.55 for any osteoporotic fracture [4].These findings permitted comparison of the calculated expected difference in mean BMD between those with, versus those without, a prior fracture, with the actual difference ascertained from the baseline data.Thus, the proportion of risk attributed to a low BMD was computed as where HR a is the unadjusted hazard ratio for prior fracture, HR b is the hazard ratio adjusted for BMD, and GR is the gradient of risk for femoral neck BMD [4].
Individuals with missing data were excluded.No data were imputed.

Sensitivity analyses
As noted above, the effect of sex on the hazard ratio for fracture was examined in those cohorts that contributed both men and women.Similarly, differences in risk with and without BMD were additionally explored in those cohorts that contributed both scenarios.Assessment of the effects of race and ethnicity was confined to those cohorts recording more than one race or ethnic group (Asian, Black, Hispanic, White), comprising Health ABC, CAMOS, MROs USA, WHI, SOF, Manitoba, and UK Biobank.Results were also computed according to study quality as previously defined [20].Quality was based on a 0/1 score for four criteria: population-based cohort (yes scores 1); fracture ascertainment (self-report scores 0, others score 1); duration of follow-up (> 2 years, scores 1); average loss to follow-up/year (< 10%, scores 1).This gives a maximum score of 4 and a minimum   3).The prevalence of recording a history of a prior fracture was higher in women than in men (OR = 1.34; 95% CI = 1.32-1.35unadjusted).

Risk of fracture by site and sex
Previous fracture was associated with a significantly increased risk of any subsequent fracture (Table 4).In men and women, the HR ranged from 1.71 to 1.99 depending upon category of the outcome fracture.There were no significant differences in hazard ratios by site of fracture.The risk ratio was marginally but not significantly higher in men than in women by approximately 7-11%.In a sensitivity analysis using only those cohorts that contributed both men and women, there was no sex difference in hazard ratio for all sites (Appendix, Table A) The increase in risk among those who reported a prior clinical fracture was fairly heterogeneous as shown in the forest plots in Fig. 1 for MOF and hip fracture outcomes.Forest plots for any clinical fracture and osteoporotic fracture outcomes are given in the Appendix.Heterogeneity was not related to the question construct since the question construct had little effect on the outcome.In the case of an osteoporotic fracture, for example, the question construct of any prior fracture was associated with a similar increase in fracture risk (HR = 1.87; 95%CI = 1.58-2.22)as that when the question referred to a prior major osteoporotic fracture (HR = 1.77; 95%CI = 1.51-2.07)or where the site of prior fracture was unspecified (HR = 1.75; 95%CI = 1.61-1.89).Similarly, there was no significant difference when low or moderate trauma was specified (HR = 1.77; 95%CI = 1.41-2.22)or unspecified (HR = 1.84; 95%CI = 1.67-2.03;p > 0.3).

Dependence on BMD
The impact of BMD on the fracture risk in individuals with a prior fracture is quantified in Table 5.The HR

Hip fracture
Hazard raƟo and 95% CI Major osteoporoƟc fracture Hazard raƟo and 95% CI Fig. 1 Forest plot showing effect size on hip fracture risk (left panel) and major osteoporotic fracture (right panel) associated with a prior fracture in men and women combined adjusted for age and time since baseline was marginally decreased by approximately 8-16% when account was taken of BMD.In the case of any clinical fracture, if it is assumed that the risk of any clinicalfracture increases 1.45-fold for each standard deviation (SD) decrease in hip BMD (gradient of risk), then the difference in risk between those with and without a prior fracture is equal to an expected difference in BMD of 1.57SD [log 1.79/log1.45].In reality, the difference in BMD at all ages in men and women combined was approximately 0.22 SD ([log (1.79)/log(1.45)]− [log(1.65)/log(1.45)]).Thus, low BMD accounted for the minority (14%; 0.22/1.57) of the difference in risk of any clinical fracture between those with or without a prior fracture.As would be expected, the proportion of risk accounted for by BMD was greater in the case of hip fractures (see Table 5) but remained less than 50% (see Table 5).

Interaction with age
A prior fracture history was a significant risk factor for fracture at all ages.The hazard ratio was highest at younger ages and decreased progressively with age (Table 6).The interaction term was significant for all fracture outcomes in men and women combined.The decrease with age was most marked for hip fracture which decreased by approximately 16% for each decade of age (Fig. 2).An almost identical relationship was observed using piece-wise linear regression (data not shown).

Interaction with time
Fracture risk associated with a prior fracture decreased slowly with time since baseline by about 2-4% per year (Table 7).A similar relationship was observed using piecewise linear regression (data not shown).

Race and ethnicity
With one exception, there was no difference in the HR by race and ethnicity in those cohorts where race or ethnicity

Quality scores
There was no significant difference in fracture outcomes when cohorts of high quality were compared with those of moderate quality (Appendix, Table C).For cohorts of low quality, there was a significant difference from highquality cohorts for MOF, based on a single low-quality cohort (GERICO).

Risk of death
A prior fracture was associated with a significant increase in the risk of death in both men (HR = 1.11; 95%CI = 1.02, 1.21) and women (HR = 1.10; 95%CI = 1.05-1.15).Hazard ratios remained unchanged when adjusted for femoral neck BMD.

Discussion
The present study represents the largest meta-analysis to date on the association between prior fracture and subsequent fracture risk.The effect is similar in men and women and is consistent with our previous meta-analyses   [4].It is of interest that the quantum of effect was not dependent on the question construct.The size of the effect was also relatively immune to cohort quality and different races and ethnicities.Nonetheless, the true effect size relies on the accuracy of information provided which cannot be assessed in the construct of the present study.For the purposes of risk assessment, however, accuracy and causality of associations are of less concern than repeatability, and that the risk identified shows reversibility of effect [17,26].
The extensive data resource permitted the elucidation of important interactions comprising an interaction with age and time since baseline.For all fracture outcomes, the risk ratios decreased significantly with age, consistent with our previous meta-analysis [4] and incorporated into FRAX [17].Of importance, we were able to examine the risk associated with prior fractures among the oldest old.Additionally, the increased power of the present study revealed that hazard ratios also decreased significantly with time, a phenomenon not accounted for in the current FRAX model [17].As with all risk variables used in FRAX, any interaction of effect over time is also important to incorporate in future probability models.
The present study also quantified the independent contributions of low BMD and prior fracture.For all outcomes studied, low BMD explained a minority of the total risk.The mechanism for the BMD-independent increase in risk could not be determined from this study but is likely due, in part, to coexisting morbidity that might increase the risk of falls or impair the protective responses to injury [26,27].In addition, changes in the structural or material properties of bone may weaken bone out of proportion to any effect on BMD [28][29][30][31][32][33].
A particular strength of the present study is that the estimate of risk is made in an international setting largely from population-based cohorts.Calculations were based on the primary data, decreasing the risk of publication biases.The consistency of the association between cohorts additionally indicates the international validity of this risk variable.The present study has several limitations that should be mentioned.As with nearly all population-based studies, nonresponse biases may have occurred, which we were unable to document for all cohorts.The effect is likely to exclude sicker members of society, including those in institutional care, and may underestimate the absolute risk of fracture.Thus, the probability of a prior fracture may be underestimated from a societal perspective, but this is unlikely to affect risk ratios.The greatest potential problem was the construct of the question concerning prior fractures and the methods of documenting and characterizing subsequent fracture events.These differed substantially between cohorts.The effect of this heterogeneity on fracture outcomes was, however, marginal.It should also be recognized that additional factors affect the risk associated with a prior fracture.The increase in risk is more marked the greater the number of prior fractures [34][35][36], particularly prior vertebral fractures for a subsequent vertebral fracture [34,[37][38][39][40]. Also, the risk of a subsequent osteoporotic fracture is particularly acute immediately after an index fracture and wanes progressively with time [3,[41][42][43].For example, after a fracture, the risk of subsequent fracture is highest in the immediate post fracture interval with more than one-third of subsequent fractures occurring within 1 year [44].The waning of risk with time is also age dependent [43].Also, the effect of recency is site dependent [45] with higher risk ratios for hip and vertebral fracture than for humerus, forearm, or minor osteoporotic fracture.Finally, morphometric but subclinical fractures were not assessed though they do add to fracture probability independently of FRAX [46].Data on these additional modulating factors were not available for this meta-analysis; thus, residual confounding could be present in our findings.However, adjustments to FRAX probabilities for these factors are available through FRAXplus [47].FRAXplus, which has recently been released in a beta version, brings together a number of adjustments that can illustrate the potential impact of modulating factors on FRAX fracture probabilities.These include trabecular bone score, recency of fracture (by site and time within the last 2 years), the number of self-reported falls in the previous year, glucocorticoid dose, and duration of type 2 diabetes mellitus.An additional limitation is that no account was taken of treatment effects.
In conclusion, this analysis has quantified the magnitude of the risk for future fractures conferred by a prior fracture in the largest meta-analysis conducted to date, and that this risk is largely independent of BMD.The effect is similar in men and women.The consistency of the association in an international setting provides the rationale for the use of these data in the next iteration of FRAX.

Declarations
Ethics approval All individual cohorts with candidate risk factors available have been approved by their local ethics committees and informed consent has been obtained from all study participants.General ethics approval for the use of these cohorts is also given by the University of Sheffield.Participant data will be stored in coded, de-identified form.
Only summary statistics and aggregate data will be published, not allowing for identification of individual study participants.
Consent to participate All individual cohorts with candidate risk factors available have been approved by their local ethics committees and informed consent has been obtained from all study participants.General ethics approval for the use of these cohorts is also given by the University of Sheffield.

Fig. 2
Fig.2Hazard ratio (HR) and 95% confidence interval of a major osteoporotic fracture (MOF) and hip fracture by age associated with a history of prior fracture in men and women combined.HRs are adjusted for time since baseline and sex

Fig. 3
Fig. 3 Forest plot showing effect size on osteoporotic fracture risk (left panel) and any clinical fracture (right panel) associated with a prior fracture in men and women combined adjusted for age and time since baseline

Table 1
Characteristics association of prior fracture and fracture risk changed with age.Interactions with time and with age were also explored using piece-wise linear regression to check the adequacy of the Poisson model.The hazard ratio (HR) for previous fracture was determined for each age from 40 years from the Poisson model.Results of each cohort and the two sexes were weighted according to the variance and merged to determine the weighted means and standard deviations.

Table 3
Prevalence of a prior fracture history in men and women by age.The Manitoba and Maccabi data are not included since primary data were not available

Table 2
Details of the construct of the questionnaire on fracture type and history in the cohorts studied Element Construct Time horizon Ever in life, adult life, from age 18, 20, 35, 40, 45, 50, past 12 months, 5 years or 10 years Site of fracture Any fracture, osteoporotic fracture, MOF Energy All trauma included, moderate trauma, low trauma Validity Self-reported, verified, based on GP medical record, administrative healthcare data, has a doctor/nurse/physician assistant told you?Vertebral deformity Vertebral fractures assessed by semiquantitative criteria included, not included

Table 5
Hazard ratio (HR) and 95% confidence interval (CI) of fracture at the sites indicated associated with a history of prior fracture in men and women combined.HRs are adjusted for age and time since baseline and additionally adjusted for BMD where indicated.The last column indicates the proportion of risk explained by BMD The effect was largely driven by a high HR in Blacks from Manitoba (HR = 5.34, 95% CI = 1.79-15.94)Fig.3.

Table 8 Hazard
AcknowledgementsWe are grateful to Dr. Östen Ljunggren for contributing the MrOS Sweden cohort.UK Biobank data are included under approved access agreement 3593.The authors acknowledge the Manitoba Centre for Health Policy for use of Manitoba data contained in the Population Health Research Data Repository (HIPC 2016/2017-29).The results and conclusions are those of the authors and no official endorsement by the Manitoba Centre for Health Policy, Manitoba Health, Seniors and Active Living, or other data providers is or should be inferred.

Table 10
Hazard ratio (HR) and 95% confidence interval (CI) of fracture at the sites indicated associated with a history of prior fracture in men and women combined according to quality score.HRs are adjusted for age and time since baseline Conflict of interest J.A.Kanisled the team that developed FRAX as director of the WHO Collaborating Centre for Metabolic Bone Diseases.E.V. McCloskey, W.D. Leslie, M. Lorentzon, N.C.Harvey, E. Liu, L. Vandenput, and H. Johansson are members of the FRAX team.J.A. Kanis, N.C.Harvey, and E.V. McCloskey are members of the advisory body to the National Osteoporosis Guideline Group.J.A. Kanis reports no additional competing interests.K.E.Åkesson has no financial interest related to FRAX; chaired the National SALAR Group for Person-Centered Care Pathway Osteoporosis.F.A. Anderson led the team that developed GLOW, while director of the Center for Outcomes Research at the University of Massachusetts Medical School; he has no financial interest in FRAX.R. Azagra has received funding for research from Instituto Carlos III of Spanish Ministry of Health, IDIAP Jordi Gol of Catalan Government, and from Scientific Societies SEMFYC and SEI-OMM.C.L. Bager is employed at Nordic Bioscience and owns stock in Nordic Bioscience.She declares no competing interests in relation to this work.H.A. Bischoff-Ferrari has no financial interest in FRAX.For the DO-HEALTH trial cohort, Prof. Bischoff-Ferrari reports independent and investigator-initiated grants from European Commission Framework 7 Research Program, from the University of Zurich, from NESTEC, from Pfizer Consumer Healthcare, from Streuli Pharma, plus non-financial support from DNP.For the study cohort extension, she reports independent and investigator-initiated grants from Pfizer and from Vifor.Further, Prof. Bischoff-Ferrari reports non-financial support from Roche Diagnostics and personal fees from Wild, Sandoz, Pfizer, Vifor, Mylan, Roche, Meda Pharma, outside the submitted work with regard to speaker fees and travel fees.J.R. Center has received honoraria for speaking at educational meetings and for advisory boards from Amgen and honoraria for an advisory board from Bayer.R. Chapurlat has no financial interest in FRAX.He has received grant funding from Amgen, UCB, Chugai, MSD, Mylan and Medac.He has received honoraria from Amgen, UCB, Chugai, Galapagos, Biocon, Abbvie, Haoma Medica, Pfizer, Amolyt, MSD, Lilly, BMS, Novartis, Arrow, PKMed, Kyowa-Kirin, and Sanofi.C. Christiansen owns stock in Nordic Bioscience.He declares no competing interests in relation to this work.C. Cooper reports personal fees from Alliance for Better Bone Health, Amgen, Eli Lilly, GSK, Medtronic, Merck, Novartis, Pfizer, Roche, Servier, Takeda.and UCB. A. Diez-Perez reports personal fees from Amgen, Lilly, Theramex and grants from Instituto Carlos III and owns shares of Active Life Scientific, all outside the submitted work.J.A. Eisman declares consulting and research support from Actavis, Amgen, Aspen, Lilly, Merck Sharp and Dohme, Novartis, Sanofi-Aventis, Servier, and Theramex.P.J.M. Elders has no financial interest in FRAX.P.J.M. Elders reports support for the SOS study by Stichting Achmea Gezondheidszorg, Achmea, and VGZ zorgverzekeraar.Additional support was given by the stichting Artsenlaboratorium en Trombosedienst.Outside the submitted work, she did receive independent investigator-driven grants by Zonmw, the Netherlands; de Hartstichting, the Netherlands; the European foundation for the study of Diabetes, Amgen, the Netherlands; TEVA, the Netherlands; and Takeda, the Netherlands.Claus-C.Glüer reports honoraria and research support from AgNovos, Amgen, Osteolabs, and UCB unrelated to this work.N.C.Harvey has received consultancy/lecture fees/honoraria/grant funding from Alliance for Better Bone Health, Amgen, MSD, Eli Lilly, Radius Health, Servier, Shire, UCB, Consilient Healthcare, and Internis Pharma.D.P. Kiel has no financial interest in FRAX but has received support for his work in the Framingham Study over the past 30 years by the National Institutes of Health, Astra Zeneca, Merck, Amgen, and Radius Health.MA Kotowicz has received funding from the National Health and Medical Research Council (NHMRC), Australia, and the Medical Research Future Fund (MRFF), Australia.He has served on advisory boards for Amgen Australia, Novartic, and Eli Lilly-all unrelated to this work, and is the Director of the Geelong Bone Densitometry Service.M. Lorentzon has received lecture fees from Amgen, Lilly, Meda, Renapharma, and UCB Pharma and consulting fees from Amgen, Radius Health, UCB Pharma, Renapharma, and Consilient Health, all outside the presented work.E.V. McCloskey has received consultancy/lecture fees/grant funding/ honoraria from AgNovos, Amgen, AstraZeneca, Consilient Healthcare, Fresenius Kabi, Gilead, GSK, Hologic, Internis, Lilly, Merck, Novartis, Pfizer, Radius Health, Redx Oncology, Roche, Sanofi Aventis, UCB, ViiV, Warner Chilcott, and I3 Innovus.C. Ohlsson is listed as a coinventor on two patent applications regarding probiotics in osteoporosis treatment.E.S. Orwoll reports consulting fees from Amgen, Biocon, Radius, and Bayer, and research support from Mereo.J.A. Pasco has received funding from the National Health and Medical Research Council (NHMRC), Australia, and the Medical Research Future Fund (MRFF), Australia, all unrelated to this work.K.M.A. Swart is an employee of the PHARMO Institute for Drug Outcomes Research.This independent research institute performs financially supported studies for government and related healthcare authorities and several pharmaceutical companies.N.C.Wright sits on the Board of Trustee of the US Bone Health and Osteoporosis Foundation and has received consulting fees from Radius and ArgenX.M.C.Zillikens has received honoraria in the past for lectures or advice from Alexion, Amgen, Eli Lilly, Kyowa Kirin, Shire, and UCB, unrelated to the current work.M. Zwart has received research funding from national societies (SEMFYC and SEIOMM).C. Beaudart, E. Biver, O. Bruyère, J.A. Cauley, C.J. Crandall, S.R. Cummings, J.A.P. da Silva, B. Dawson-Huges, A.B. Dufour, S. Ferrari, Y. Fujita, S. Fujiwara, I. Goldshtein, D. Goltzman, V. Gudnason, J. Hall, D. Hans, M. Hoff, R.J. Hollick, M. Huisman, M. Iki, S. Ish-Shalom, H. Johansson, G.Jones, M.K. Karlsson, S. Khosla, W.-P. Koh, F. Koromani, H. Kröger, T. Kwok, O. Lamy, A. Langhammer, B. Larijani, W.D. Leslie, K. Lippuner, E. Liu, D. Mellström, T. Merlijn, A. Nordström, P. Nordström, T.W. O'Neill, B. Obermayer-Pietsch, F. Rivadeneira, A.-M. Schott, E.J. Shiroma, K. Sigeirsdottir, E.M. Simonsick, E. Sornay-Rendu, R. Sund, K.M.A. Swart, P. Szulc, J. Tamaki, D.J. Torgerson, L. Vandenput, N.M. van Schoor, T.P. van Staa, J. Vila, N.J.Wareham, and N. Yoshimura declare no competing interests in relation to this work.